The Role of Long-Range Brain Connectivity in Human Language Processing

• Applicants: Professor Dr.-Ing. Fred Henrik Hamker; Professor Dr. Thomas Knösche; Professor Dr. Tilo Schwalger
• Subject Area: Human Cognitive and Systems Neuroscience ; Experimental and Theoretical Network Neuroscience
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 550758043

Sophisticated language skills are uniquely human. So far, it has not been possible to teach any non-human animal, including primates, human language beyond a primitive level with limited vocabulary and simplest syntactic structure. There is evidence that macroscopic and microscopic properties of long-range white matter fiber connections, in particular those connecting Broca’s area to parietal and temporal regions, are relevant for these skills and undergo plastic changes during training. We also know that information flows from and to Broca’s area are related to language abilities and their acquisition. Although the precise mechanism of the relationship between these phenomena is not clear, we may assume that language processing involves multiple interconnected areas throughout the brain, many of which bear substantial specialization. Within that network, a large number of word webs encodes the vocabulary. During sentence comprehension, word webs get synchronously active and undergo syntactic merging operations implementing hierarchical syntax processing. For a truly mechanistic understanding of how language processing relates to the aforementioned structural traits, it is necessary to construct a brain-wide model based on realistic cortical microcircuit dynamics and network architectures. The goal of this project is to link core computational operations that are specific to human language (verbal working memory, merging) with structural features that distinguish humans from their closest relatives, that is extensive long-range connections between frontal, parietal and temporal lobes. We hypothesize that a neuronal code based on theta-gamma coupling and attractor dynamics enables the activation of word webs as well as merge and structure building operations. We also hypothesize that fronto-parieto-temporal connections are specifically relevant for this process, and seek to elucidate the specific roles of their structural traits, such as myelination, fiber count, and fiber diameters. We will perform a language comprehension experiment that will yield rich behavioral, magnetoencephalographic, and diffusion MRI data, which will be used to specify individual whole brain models. Using a novel multiscale modeling and simulation framework based on spiking neurons, the network of interacting brain areas will be represented by mean-field models of local cortical circuits and long-range connections. Language-relevant areas will be described in a more fine-grained manner as multi-attractor networks. We will study how the language operations reproduced by the model depend on particular brain structure parameters, with focus on the aforementioned long-range white matter fiber tracts. This will allow us to draw specific conclusions on the relevance of the different fiber properties (e.g., density, diameter, myelination) and the associated dynamic phenomena (e.g., delay, synchronization, ephaptic coupling) for crucial and specifically human language operations.

• DFG Programme: Research Grants
• International Connection: Czech Republic
• Partner Organisation: Czech Science Foundation
• Cooperation Partner: Dr. Helmut Schmidt